Acoustic signal processing is applicable today to improve the quality of sound signals such as from microphones. As one example, many devices such as handsets operate in the presence of sources of echoes, e.g., loudspeakers. Furthermore, signals from microphones may occur in a noisy environment, e.g., in a car or in the presence of other noise. Furthermore, there may be sounds from interfering locations, e.g., out-of-location conversation by others, or out-of-location interference, wind, etc. Acoustic signal processing is therefore an important area for invention.
Processing systems are known for one or more of suppressing noise, suppressing echo, and adding spatial selectivity. An acoustic noise reduction system typically includes a noise estimator and a gain calculation module to determine suppression probability indicators, e.g., as a set of noise reduction gains that are determined, for example, on a set of frequency bands, and applied to the (noisy) input audio signal after transformation to the frequency domain and banding to the set of frequency bands to attenuate noise components. The acoustic noise reduction system may include one microphone input, or a plurality of microphone inputs and downmixing, e.g., beamforming to generate one input audio signal. The acoustic noise reduction system may further include echo reduction, and may further include out-of-location signal reduction.
Musical noise is known to exist, and might occur because of short term mistakes over time made on the gain in some of the bands. Such gains-in-error can be considered statistical outliers, that is, values of the gain that across a group of bands statistically lie outside an expected range, so appear “isolated.”
Such statistical outliers might occur in other types of processing in which an input audio signal is transformed and banded. Such other types of processing include perceptual domain-based leveling, perceptual domain-based dynamic range control, and perceptual domain-based dynamic equalization that takes into account the variation in the perception of audio depending on the reproduction level of the audio signal. See, for example, International Application PCT/US2004/016964, published as WO 2004111994. It is possible that the gains determined for each band for leveling and/or dynamic equalization include statistical outliers, e.g., isolated values, and such outliers might cause artifacts such as musical noise.
Median filtering the gains, e.g., noise reduction gains, or leveling and/or dynamic equalization gains across frequency bands can reduce musical noise artifacts. German Patent Application Publication DE4405723A1, also published as European Patent Publication EP0669606, describes the use of median filtering for the reduction of “musical tones” which may occur in the context of spectral subtraction.
Gain values may vary significantly across frequencies, and in such a situation, running a relatively wide median filter along frequency bands has the risk of disrupting the continuity of temporal envelope, which is the inherent property for many signals and is crucial to perception as well. Whilst offering greater immunity to the outliers, a longer median filter can reduce the spectral selectivity of the processing, and potentially introduce greater discontinuities or jumps in the gain values across frequency and time.
The approaches described in this BACKGROUND section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. Similarly, issues identified with respect to one or more approaches should not assume to have been recognized in any prior art on the basis of this section, unless otherwise indicated.